Navigating digital inclusion and the digital va among Niue mamatua through the provision of mobile phones during COVID-19.

Technology and digital platforms have become essential for people and communities to interact because of COVID-19. Despite its benefits, digital exclusion disproportionately affects Pacific communities living in New Zealand. This article provides insights into how Niue mamatua (older adults) used their gifted mobile phones and mobile data as part of a COVID-19 digital inclusion initiative. It begins with an overview of the digital inclusion needs of older adults, followed by a description of the digital va (relational space) and negotiating a new way of maintaining connection in an online world. The tutala (a Niue method of conversation anchored on respect) with 12 mamatua highlighted the benefits, support factors, and challenges of how they were able to use their mobile phone. Importantly, mobile phones provided the necessary access and connectivity to interact in a digitally connected world, namely the digital va, when in-person connections were disrupted because of COVID-19.

Evaluation of Patients at Risk of Hospital Readmission (PARR) and LACE Risk Score for New Zealand Context.

Identification and prediction of patients who are at risk of hospital readmission is a critical step towards the reduction of the potential avoidable costs for healthcare organisations. This research was focused on the evaluation of LACE Index for Readmission - Length of stay (days), Acute (emergent) admission, Charlson Comorbidity Index and number of ED visits within six months (LACE) and Patients At Risk of Hospital Readmission (PARR) using New Zealand hospital admissions. This research estimates the risk for all readmissions rather than only those in a subset of referenced conditions. In total, 213,440 admissions between 1 Jan 2015 and 31 Dec 2016 were selected after appropriate ethics approvals and permissions from the three hospitals. The evaluation method used is the Receiver Operating Characteristics (ROC) analysis to evaluate the accuracy of both the LACE and PARR models. As a result, The LACE index achieved an Area Under the Curve (AUC) score of 0.658 in predicting 30-day readmissions. The optimal cut-off for the LACE index is a score of 7 or more with sensitivity of 0.752 and specificity of 0.564. Whereas, the PARR algorithm achieved an AUC score of 0.628 in predicting 30-day readmissions. The optimal cut-off for the PARR index is a score of 0.34 or more with sensitivity of 0.714 and specificity of 0.542.